Kerry Back
model = RandomForestRegressor() cv = GridSearchCV( model, param_grid={ "max_depth": range(1, 11) }, ) _ = cv.fit(X, y)
param_grid={ "hidden_layer_sizes": [ [16, 8, 4, 2], [16, 8, 4], [8, 4, 2], [16, 8], [16, 4], [8, 4], [4, 4], [4, 2] ] }
model = MLPRegressor(max_iter=500) cv = GridSearchCV( model, param_grid=param_grid ) _ = cv.fit(X, y)
from scipy.stats import uniform u = uniform(scale=0.2) model = GradientBoostingRegressor() cv = RandomizedSearchCV( model, param_distributions={ "learning_rate": u, "max_depth": range(2, 10, 2) }, n_iter=16 ) _ = cv.fit(X, y)